Transitioning additive manufacturing from rapid prototyping to high‐volume production: A case study of complex final products

This paper seeks answers to the question: what are the key factors that enable the scaling of additive manufacturing (AM) from rapid prototyping to high‐volume production? Using a longitudinal case study, we collected primary and secondary data to trace the AM scaling journey of AeroCo, a highly inn...

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Veröffentlicht in:The Journal of product innovation management 2023-07, Vol.40 (4), p.554-576
Hauptverfasser: Roscoe, Samuel, Cousins, Paul D., Handfield, Robert
Format: Artikel
Sprache:eng
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Zusammenfassung:This paper seeks answers to the question: what are the key factors that enable the scaling of additive manufacturing (AM) from rapid prototyping to high‐volume production? Using a longitudinal case study, we collected primary and secondary data to trace the AM scaling journey of AeroCo, a highly innovative aerospace firm. Based on the case findings, we position AM as a whole system technology because it can print components for a wide range of subsystems in a complex final product. Scaling AM requires a significant realignment of existing, and often deeply entrenched, new technology, and product development processes. To achieve this alignment, AeroCo formed institutional alliances with the UK government and universities to establish university technology centers, which facilitated early stage ideation and “catapult” centers, which enabled high‐volume testing in factory‐like facilities. The case reveals how multiple functions needed to integrate, including research and development, product design, and future programs, to ensure that design changes cascaded from one subsystem to another, and that new technologies were linked to a future product to create a final product pull. These findings inform a managerial framework for additive manufacturing scaling that is generalizable to other digital technologies used in the design and production of complex final products, including artificial intelligence, machine learning, smart factories, and cyber physical production systems. Our framework contributes to innovation thought and practice by explaining how new product development processes and organizational structures change under the effect of digital technologies.
ISSN:0737-6782
1540-5885
DOI:10.1111/jpim.12673